Create app.py

app.py

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+import os
+import streamlit as st
+from transformers import pipeline
+from groq import Groq
+
+# Check if Groq API should be used
+use_groq = False  # Update this to True if you want to use Groq API
+
+# Groq setup
+if use_groq:
+    client = Groq(
+        api_key=os.environ.get("GROQ_API_KEY"),
+    )
+
+# Hugging Face model setup using pipeline
+pipe = pipeline("text-generation", model="RayyanAhmed9477/Health-Chatbot")
+
+# Streamlit app setup
+st.title("Healthcare Chatbot")
+st.write("Ask me anything related to healthcare!")
+
+user_input = st.text_input("Your Question:")
+
+if user_input:
+    # If Groq API is to be used, modify this accordingly
+    if use_groq:
+        chat_completion = client.chat.completions.create(
+            messages=[
+                {"role": "user", "content": user_input}
+            ],
+            model="RayyanAhmed9477/Health-Chatbot",
+        )
+        st.write(chat_completion.choices[0].message.content)
+    else:
+        # If Groq is not being used, directly use Hugging Face pipeline
+        messages = [{"role": "user", "content": user_input}]
+        response = pipe(messages)
+        st.write(response[0]["generated_text"])